Gait-based person identification by spectral, cepstral and energy-related audio features

Jurgen T. Geiger, Martin Hofmann, Bjorn Schuller, Gerhard Rigoll

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

14 Zitate (Scopus)

Abstract

With this work, we address the problem of acoustic gait-based person identification, which is the task of identifying humans by the sounds they make while walking. We examine several acoustic features from speech processing tasks for their suitability for acoustic gait recognition. Using a wrapper-based feature selection technique, we reduce the feature set while at the same time increasing the identification accuracy by 10% (relative). For classification, Support Vector Machines (SVMs) are employed. Experiments are conducted using the TUM GAID database, which is a large gait recognition database containing 3 050 recordings of 305 subjects in three variations.

OriginalspracheEnglisch
Titel2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Seiten458-462
Seitenumfang5
DOIs
PublikationsstatusVeröffentlicht - 18 Okt. 2013
Veranstaltung2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Kanada
Dauer: 26 Mai 201331 Mai 2013

Publikationsreihe

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Konferenz

Konferenz2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Land/GebietKanada
OrtVancouver, BC
Zeitraum26/05/1331/05/13

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